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Informatica MDM is one of the most popular Master Data Management software that allows management and organisation of data through a single unified platform. The data management software is safe and reliable. Informatica MDM gives an insight into relationships with customers, products, and the related data streamlining data management to drive towards success.
Below is a curated list of Informatica MDM interview questions most frequently asked by the interviewers in an Informatica MDM interview process covering topics from a Beginners to Advanced level.
Ans: Master Data Management(MDM) is a methodology that allows the organization to link all its essential data into a single file, which is called a master file. This file seems to be a standard base reference to the organization that helps to make crucial business decisions. Master Data Management acts as a network to share the data among various firms.
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The term MDM (Master Data Management)refers to a comprehensive method that helps an enterprise to link its entire critical data to a single, master file serving as a common point of reference. Informatica’s Master Data Management simplifies data sharing across departments and members.
Ans: The following are the different components of PowerCenter:
Ans: The data warehouse is the primary method of managing and gathering information from various sources to assist the firms with helpful insights. Using a Data warehouse, you can analyze and integrate the data from various sources. A data warehouse is connected with different technologies and components that allow the firms to utilize the data in a well-organised process. It collects all the information in a digital form for further interpretation and moulds the data into an understandable way and makes it feasible for business users.
Ans: following are the various four fundamental phases of data warehousing. They are:
Now, let us know about each phase of the data warehouse with useful insights.
Offline Operational Databases: This is the initial stage of the data warehouse, evolved from copying the original operating system into an offline server. This process doesn’t impact the performance of the system.
Offline Data Warehouse: In this phase, data warehouses update the operational data regularly such as daily, weekly, and monthly and the data is stored in an homogenous report oriented way.
Real-time Data Warehouse: In this phase, the operating system executes an action or an event every time and updates the events in the data warehouse.
Integrated Data Warehouse: In this last phase, data warehouses generate transactions and activities that pass through the OS, which assists the organization in daily business functionality.
Ans: Every technical folk need to face challenges when they are selling a project and getting the funds. Management is actively looking for ROI, and they need MDM to be quantifiable advantages and profits for their business.
Ans: In dimensional modelling, there are two tables which are distinct from the third normal form. In this model, fact tables used for business measurements and the dimension table contain a context.
Ans: Dimension table is a compilation of logic, categories, and hierarchies, which can be used for a further traverse in hierarchy nodes by a user. And the dimension table contains textual measurements stored in fact tables.
Ans: There are two methods to load the data in dimension tables. Following are the two methods:
Ans: In a data warehouse, a fact table consists of two columns which include metrics and measurements of business methods and foreign key. It is determined at the center of the star or snowflake schema surrounded by dimension tables.
Ans: Mapping represents the flow of data between the sources and targets. It is a set of target definitions and source linked by transformation objects that defines the data transformation rules.
Ans: Mapplet is a reusable element that consists set of changes that allow reusing that transformation logic in involved mappings.
Ans: It is a repository element that helps to generate and modifies the data. In mapping, transformation represents certain operations that perform on integrated services. All the data that passes through these transformation ports linked with mapping.
Ans: Data Mining is the process of analysing the vast amount of data to find valuable hidden insights and compiling it into useful data. It allows the users to discover unknown relationships and patterns between various elements in the data. The useful insights extracted from the data might help you in scientific discovery, marketing, fraud detection, and many more.
Ans: Following are the various objects that cannot use in the mapplets:
Ans: In fact table, foreign keys are the primary key of the dimensional table, and in the dimensional table, foreign keys are the primary key of the entity table.
Ans: Following are the different ways used in Informatica to switch one environment to another:
Ans:
Ans: Following are the different ways to delete the duplicate records from Informatica:
Ans: Using the following query, you can find invalid mappings in a folder:
SELECT MAPPING_NAME FROM REP_ALL_MAPPINGS WHERE
SUBJECT_AREA='YOUR_FOLDER_NAME' AND PARENT_MAPPING_IS_VALIED <>1
Ans: Here are the various types of repositories that you can create in Informatica.
Ans: Data movement modes provide a set of instructions to handle the process of character data. Based on that, you can determine the data movement from Informatica server configuration settings. Here are the two data movement modes:
Ans: Following are the two types of locks used in Informatica MDM 10.1:
Ans: Following are the list of various tools that are not required lock:
Ans: Following are the tools that are required Lock to make configuration amends to the database of MDM hub master in Informatica MDM:
Ans:
Ans: For every 60 seconds the hub console is refreshed in the current situation. Lock can be released by the users manually. If a user switches to another database while the lock is on hold, the lock will be released automatically. The lock expires within a minute if the user terminates the hub console.
Ans: Following are the components of Informatica hub console:
Ans: Following are the multiple tables that can integrate with the staging data in MDM. They are:
Ans: Following are the various stages in which data is stored into hub stores in a sequential process.
Ans: Informatica Powercenter is a data integration software which is developed by Informatica Corporation. It is a widely used ETL tool (Extract, Transform, Load) to build organization data warehouses. The components of Informatica PowerCenter assists in extracting the data from multiple sources, transforming the data according to the business requirements and loading it into targeted data warehouses.
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Some of the most difficult challenges in adopting MDM include:
Data warehouses are a trove of information updated periodically. Data warehouses play a key role in the decision making of any business as it contains all the data relating to processes, transactions, etc., of a company and serves as a deciding factor. Data warehousing allows data analysts to perform analysis, and execute complex queries on structured data sets and also conduct data mining. Data warehouses help identify the current position of the business by comparing all factors.
Dimensional modeling is an important data structure technique to optimise data storage in data warehouses. Dimensional modeling includes Facts tables and Dimension tables determining measurements of the business (Facts table) and dimensions and other calculations of the measurement (Dimension table).
The data warehousing stages play an integral role in determining the changes in data in the warehouse. The fundamental stages data warehousing are:
Informatica PowerCenter is an ETL (Extract, Transform, and Load)tool used for enterprise data warehouses. PowerCenter helps extract data from the selected source, transforms it, and loads into the chosen data warehouse. Informatica PowerCenter consists of client tools, a server, a repository, and a repository server as its core components. It executes tasks generated by the workflow manager and allows mapping using the mapping designer.
There are many components that form the foundation of Informatica PowerCenter. They include:
Mapping can be described as a set of target definitions and sources that are connected with transformation objects that define data transformation rules. Mapping represents the flow of data between the targets and sources.
A Mapplet is a reusable object consisting of transformations which can be reused in multiple mappings. A Mapplet can be created in the Mapplet Designer.
Informatica transformations are objects in the repository capable of reading, modifying, or passing data to defined targeted structures such as tables, files, etc,. Transformations represent a set of rules determining data flow and data loading into targets.
Data Mining is also known as knowledge discovery in data (KDD) for the reason that it involves sorting through and performing complex analysis procedures on multiple data sets to discover underlying information crucial for business growth.
In data warehousing, a fact table is present at the centre of a star scheme and contains quantitative information relating to metrics, measurements, or facts of a business process.
A dimension table is a part of the star, snowflake, or starflake schema in data warehousing. Dimension tables contain measurement of a fact and are connected to the fact table. The dimension tables form an integral component of dimensional modelling.
The dimension tables must contain a primary key which corresponds to a foreign key in a fact table and a fact table must contain a primary key that corresponds with the foreign key in the dimension tables.
The methods of loading dimension tables are:
Objects that cannot be used in a mapplet include:
The following are the ways to migrate from one environment to another in Informatica:
Duplicate records can be deleted from Informatica by:
There are four types of repositories that can be generated using Informatica Repository Manager:
The invalid mappings in a folder can be found using the below mentioned query:
SELECT MAPPING_NAME FROM REP_ALL_MAPPINGS WHERE
SUBJECT_AREA='YOUR_FOLDER_NAME' AND PARENT_MAPPING_IS_VALIED <>1
Data movement mode enables the Informatica server to handle the character data. The data movement modes can be selected in the Informatica server configuration settings. There are two modes of data movement in Informatica:
OLTP is the abbreviation of Online Transaction Processing. OLTP involves capturing, storing and processing data from multiple transactions in real-time. All the transaction data is stored in a database.
In Informatica, the parallel degree of data loading properties clarify the degree of parallelism set on the base object table and other related tables. Though it does not affect all the batch processes, it has a significant effect on the performance when used. The use of parallel degree depends on the number of CPUs on the database and available memory. The default parallelism value is 1.
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Informatica MDM 10.1 ha two types of LOCK:
The hub console is refreshed in the current connection every minute i.e, every 60 seconds. A lock can be manually released by a user. If a user switches to another database while holding a lock, the lock is released automatically. If a user terminates the hub console, the lock expires after one minute.
Tools which do not require Lock in Informatica include:
In Informatica, some tools require LOCK to make configuration changes to the database of the Hub Master in MDM. These tools are:
The tables linked with staging data in Informatica are:
OLAP (Online Analytical Processing) software performs multidimensional analysis on large volumes of data. It collects, processes, manages, and presents data for analysis and management.
The data from different sources undergoes complex processing and the processes in Informatica include:
The stage process involves the transfer of source data from the landing tables to the stage tables. The stage process is completed using the stage mapping between the landing table and the stage table. Data cleansing and standardisation is also done during the stage process.
With this article, we aim to target the most frequently asked interview questions and encourage learners to make the most out of the answers listed above to clear the interview with maximum knowledge and confidence. In case we have missed an important question, please mention it in the comments so that we update it in the article.
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